Combining our deep industry knowledge with data and AI capabilities and Databricks expertise, we proposed an AI-driven ESG audit solution. This intelligent automation solution provided a modern, unified data ecosystem with AI capabilities to fortify the firm’s existing ESG audit processes.
Databricks’ scalable environment fulfilled the need for fast and seamless ingestion of large volumes of CSR documents in diverse formats and integration of all data for efficient analysis. Further, it also allowed our data experts to easily integrate advanced analytics tools, machine learning algorithms, and NLP techniques to drive a range of automated audit features and eliminate the redundancies of manual mechanisms.
The new ESG audit solution offered automated information mining and scoping for GRI/SASB ESG Standards, Topics, Disclosures, and Requirements. It presented top-recommended contextually matching phrases from the CSR documents for a data-driven ESG confidence score and also generated ESG taxonomy from audit documents for robust data evidence.
Databricks provided a collaborative platform with feedback ingestion capabilities for the auditors to easily add information from their subject matter expertise to ML suggestions and build a robust foundation for future ESG audits. On a single platform, the auditors could now analyze and extract Quality XRef data from historic audits to gain insights into how specific ESG criteria were previously evaluated, documented, and measured. Additionally, with features such as interactive Q&A assistance, auditors could even ask questions in the free-flow text to find contextually matching answers.